code: def _parallel_augment(cls, action_fx, data, n, num_thread=2):
      pool = ThreadPool(num_thread)
      results = pool.map(action_fx, [data] * n)
      pool.close()
      pool.join()
      return results
  
imports: import math
  import random
  import numpy
  import pandas
  from multiprocessing.dummy import Pool
  from nlpaug.util import Action, Method, WarningException, WarningName, WarningCode, WarningMessage
label_desc: Use image node_id 5 for calling the Augmenter obj's underlying member method code with example usage: obj._parallel_augment(cls, action_fx, data, n, num_thread) and returns: results